Bridging Data and Decision-Making: Data Visualization Techniques with R

Nnamdi Azikwe University

Ifeoma Egbogah

Data

What is Data?

Data Types

Numerical

Data Types Contd

Categorical

Why Data Visualization Matters

  • Humans process visuals 60,000x faster than text

  • Visuals simplify complex data

  • Helps identify trends, outliers, and patterns

  • Supports data-driven decisions

Real-World Example:

COVID-19 dashboards helped governments track and respond to infection spikes and vaccinations.

Bridging the Gap Between Data and Decisions

Problem: Data is abundant, but insights are scarce.

Solution: Visualization bridges the gap between raw data and strategic action.

Outcome: Simplifies storytelling and supports real-time decisions.

What is R and Why Use It?

R

  • Free and open-source statistical language

  • Used in academia and business

  • Integrates data wrangling, analysis, and visualization

Key Visualization Packages:

ggplot2

plotly

shiny

Data Visualization

Understanding Visualization Types

Chart Type Best For
Line Chart Trends over time
Bar Chart Comparing categories
Scatter Plot Correlations, relationships
Maps Geospatial data
Dashboard Monitoring KPIs in real-time

Tip: Choose simplicity and clarity over complexity.

Case Study

Academic Use Case – Education Access

Dataset: World Bank (Literacy vs Internet Access)

Visualization: Scatter plot showing socio-economic development.

Insight: Nigeria lags behind Kenya and Egypt in internet penetration despite comparable literacy rates.